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中华妇幼临床医学杂志(电子版)

Chinese Journal of Obstetrics & Gynecology and Pediatrics(Electronic Edition) ›› 2023, Vol. 19 ›› Issue (06): 734 -744. doi: 10.3877/cma.j.issn.1673-5250.2023.06.016

Original Article

Construction of a prognostic nomogram model and risk stratification system for cervical cancer patients with intensity modulated radiation therapy and after-loading therapy

Yuan Wu1, Biqing Zhu2, Dan He2, Hairong Wang2, Qian Li2,†()   

  1. 1. Department of Internal Medicine, Jiangsu Cancer Hospital / Jiangsu Institute of Cancer Research/Affiliated Cancer Hospital of Nanjing Medical University, Nanjing 210009, Jiangsu Province, China
    2. Department of Radiotherapy, Jiangsu Cancer Hospital / Jiangsu Institute of Cancer Research / Affiliated Cancer Hospital of Nanjing Medical University, Nanjing 210009, Jiangsu Province, China
  • Received:2023-01-10 Revised:2023-08-20 Published:2023-12-01
  • Corresponding author: Qian Li
  • Supported by:
    Jiangsu Provincial Maternal and Child Health Research Project(F201870)
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Objective

To explore the method of constructing a prognostic nomogram prediction model for cervical cancer patients with intensity modulated radiation therapy (IMRT) and after-loading therapy, and establish prognostic risk stratification system based on this model.

Methods

A total of 258 cervical cancer patients who received IMRT and after-loading therapy in Jiangsu Cancer Hospital / Jiangsu Institute of Cancer Research / Affiliated Cancer Hospital of Nanjing Medical University from June 2015 to December 2016 were selected as study subjects. Kaplan-Meier method was used to plot the overall survival (OS) curves of cervical cancer patients with different clinical factors, and Log-rank test was used for comparison. Multiple Cox proportional risk regression analysis was used to screen independent risk factors that affect the prognosis of cervical cancer patients receiving IMRT and after-loading therapy, and rms package of R software was used to build nomogram prediction model, and receiver operating characteristic (ROC) curve and area under curve (AUC) and calibration curve were used to evaluate the predictive performance of the nomogram prediction model for predicting the prognosis of cervical cancer patients receiving IMRT and after-loading therapy. The recursive partition analysis (RPA) method was used to predict individual risk scores of cervical cancer patients receiving IMRT and after-loading therapy based on nomogram model, and prognostic risk stratification system of cervical cancer patients was constructed. The procedures followed in this study complied with the regulations of the Ethics Committee of Jiangsu Cancer Hospital and have been reviewed and approved by the Ethics Committee (Approval No. 2023-017). All patients signed clinical research consent form.

Results

①Among 258 cervical cancer patients, complete remission (CR) rate after IMRT and after-loading therapy was 74.4% (192/258), partial remission (PR) rate was 20.9% (54/258), and total clinical effective rate was 95.3% (246/258). ②The 1-year, 3-year, and 5-year OS rates of 258 cervical cancer patients were 93.8%, 79.5%, and 64.0%, respectively. Univariate analysis of prognostic factors for cervical cancer patients by Log-rank test showed that age (χ2=4.25, P=0.039), pathological type (χ2=15.41, P<0.001), International Federation of Gynecology and Obstetrics (FIGO) stage (χ2=22.17, P<0.001), with or without lymph node metastasis (χ2=28.37, P<0.001), concurrent chemotherapy (χ2=10.99, P=0.004), induction and sequential chemotherapy (χ2=14.34, P<0.001), and short-term efficacy of IMRT and after-loading therapy (χ2=68.67, P<0.001) were all factors affecting the prognosis of cervical cancer patients receiving IMRT and after-loading therapy (χ2=68.672, P<0.001). ③Results of multivariate Cox proportional risk regression analysis showed that non squamous cell carcinoma cervical cancer patients (HR=2.404, 95%CI: 2.305-3.577, P=0.005), FIGO stages Ⅲ and Ⅳ (HR=2.455, 5.374; 95%CI: 2.386-3.609, 3.221-6.507; P=0.006, <0.001), with lymph node metastasis (HR=4.325, 95%CI: 2.189-6.420, P<0.001), lack of concurrent chemotherapy (HR=1.730, 95%CI: 1.359-2.811, P=0.040), PR and no response after IMRT and after-loading therapy were all independent risk factors affecting the prognosis of cervical cancer patients receiving IMRT and after-loading therapy. ④Nomogram prediction model was constructed based on results of the above multivariate Cox proportional risk regression analysis to predict the prognosis of cervical cancer patients receiving IMRT and after-loading therapy. ROC-AUC of the nomogram prediction model for predicting 3-year and 5-year OS rates of cervical cancer patients receiving IMRT and after-loading therapy were 0.827 (95%CI: 0.731-0.923, P<0.001) and 0.789 (95%CI: 0.695-0.883, P<0.001), respectively, indicating that the prediction model had high discriminability for 3-year and 5-year OS rates of cervical cancer patients receiving IMRT and after-loading therapy. The calibration curve analysis results of the predicted model showed that the calibration curves of 3-year and 5-year OS rates of cervical cancer patients receiving IMRT and after-loading therapy were close to the ideal curves, and the fitting was well reflected, indicating that the predicted 3-year OS rates of cervical cancer patients receiving IMRT and after-loading therapy were relatively consistent with the actual OS rates, and the calibration was good. ⑤Based on the risk score of cervical cancer patients predicted by the nomogram prediction model, prognostic risk stratification system for cervical cancer patients was constructed with the RPA method, in which all cervical cancer patients were divided into four groups: extremely low risk group (risk score<138 points), low risk group (138 points≤risk score<214 points), medium risk group (214 points≤risk score<274 points), and high risk group (risk score≥274 points). Validation results among cervical cancer patients with different FIGO stages showed that the risk stratification system can distinguish the 3-year and 5-year OS rates of the extremely low risk group, low risk group, medium risk group, and high risk group in FIGO stage Ⅱ-Ⅳ cervical cancer patients, and all differences were statistically significant (P<0.05).

Conclusions

This study constructs nomogram prediction model for predicting the prognosis of cervical cancer patients treated with IMRT and after-loading therapy based on five factors: pathological type, FIGO staging, with lymph node metastasis, concurrent chemotherapy, and short-term efficacy of IMRT and after-loading therapy, and the model has good discrimination and calibration, and can effectively predict the prognosis of cervical cancer patients after treatment of IMRT and after-loading therapy. The prognostic risk stratification system for cervical cancer patients constructed based on this prediction model has certain clinical value.

Key words: Uterine cervical neoplasms, Intensity modulated radiation therapy, After-loading therapy, Prognosis, Nomograms, Hazard stratification system, Proportional hazards models, Female
图1 本研究258例不同临床因素宫颈癌患者的OS曲线分析(图1A：年龄<65岁与≥65岁宫颈癌患者OS曲线；图1B：鳞状上皮宫颈癌与非鳞状上皮宫颈癌患者OS曲线；图1C：FIGO临床分期为ⅠB、ⅡA、ⅡB、ⅢA、ⅢB、ⅣA期宫颈癌患者OS曲线；图1D：未伴淋巴结转移与伴淋巴结转移宫颈癌患者OS曲线；图1E：同期未采取化疗与同期采取单药、双药联合化疗宫颈癌患者OS曲线；图1F：未采取诱导＋序贯化疗与采取1～2、3～7个疗程诱导＋序贯化疗宫颈癌患者OS曲线；图1G：采取IMRT＋后装治疗后达CR、PR与未缓解宫颈癌患者OS曲线) 注：OS为总体生存。FIGO为国际妇产科联盟，CR为完全缓解，PR为部分缓解，IMRT为调强放疗
表1 本研究258例不同临床因素宫颈癌患者的1、3、5年OS率比较[例数(%)]
临床因素 例数 OS χ2值a P值a
1年 3年 5年
年龄(岁)         4.25 0.039
<65 192 184(95.8) 160(83.3) 128(66.7)    
≥65 66 58(87.9) 45(68.2) 37(56.1)    
病理学类型         15.41 <0.001
鳞状上皮宫颈癌 231 219(94.8) 194(84.0) 157(68.0)    
非鳞状上皮宫颈癌 27 23(85.2) 11(40.7) 8(29.6)    
FIGO临床分期(期)         22.17 <0.001
ⅠB 24 24(100.0) 24(100.0) 19(79.2)    
ⅡA 33 31(93.9) 29(87.9) 27(81.8)    
ⅡB 109 107(98.2) 98(89.9) 77(70.6)    
ⅢA 20 19(95.0) 15(75.0) 11(55.0)    
ⅢB 50 43(86.0) 28(56.0) 23(46.0)    
ⅣA 22 18(81.8) 11(50.0) 8(36.4)    
是否伴淋巴结转移         28.37 <0.001
否 140 135(96.4) 124(88.6) 110(78.6)    
是 118 107(93.3) 81(74.2) 55(60.7)    
是否同期化疗及方案         10.99 0.004
否 42 36(85.7) 28(66.7) 18(42.9)    
单药化疗 97 92(94.8) 79(81.4) 62(63.9)    
双药联合化疗 119 114(95.8) 98(82.4) 85(71.43)    
是否诱导＋序贯化疗及疗程         14.34 <0.001
否 51 45(88.2) 36(70.6) 21(41.2)    
1～2个疗程 61 56(91.8) 48(78.7) 43(70.5)    
3～7个疗程 146 141(96.6) 121(82.9) 101(69.2)    
采取IMRT＋后装治疗的近期疗效         68.67 <0.001
CR 192 191(99.5) 182(94.8) 150(78.1)    
PR 54 49(90.7) 23(42.6) 15(27.8)    
未缓解 12 2(16.7) 0(0) 0(0)    
表2 采取IMRT＋后装治疗宫颈癌患者预后影响因素的多因素Cox比例风险回归分析结果
影响因素 B SE Wald值 P值 HR值 HR值95%CI
年龄≥65岁(vs年龄<65岁) 1.067 0.718 2.208 0.364 2.906 0.669～4.232
非鳞状上皮宫颈癌(vs鳞状上皮宫颈癌) 0.877 0.323 7.372 0.005 2.404 2.305～3.577
FIGO临床分期(vs FIGO临床分期为Ⅰ期)            
Ⅱ期 1.558 1.081 2.077 0.570 4.748 0.330～5.810
Ⅲ期 0.898 0.336 7.143 0.006 2.455 2.386～3.609
Ⅳ期 1.682 0.532 9.996 <0.001 5.374 3.221～6.507
伴淋巴结转移(vs未伴淋巴结转移) 1.464 0.476 9.459 <0.001 4.325 2.189～6.420
同期化疗情况(vs同期采取双药联合化疗)            
同期采取单药化疗 0.359 0.211 2.895 0.101 1.432 0.578～2.024
同期未采取化疗 0.548 0.254 4.655 0.040 1.730 1.359～2.811
诱导＋序贯化疗情况(vs诱导＋序贯化疗3～7个疗程)            
诱导＋序贯化疗1～2个疗程 0.948 0.604 2.463 0.252 2.580 0.494～3.228
未采取诱导＋序贯化疗 0.071 0.040 3.151 0.070 1.074 0.329～2.880
采取IMRT＋后装治疗的近期疗效(vs CR)            
PR 0.576 0.269 4.585 0.047 1.779 1.424～2.888
未缓解 1.172 0.396 8.759 <0.001 3.227 3.100～5.317
图2 采取IMRT＋后装治疗宫颈癌患者的预后列线图预测模型 注：IMRT为调强放疗。FIGO为国际妇产科联盟，CR为完全缓解，PR为部分缓解，OS为总体生存
图3 采取IMRT＋后装治疗宫颈癌患者的预后列线图预测模型预测宫颈癌患者3、5年OS率的ROC曲线(图3A：预测宫颈癌患者3年OS率的ROC曲线；图3B：预测宫颈癌患者5年OS率的ROC曲线) 注：IMRT为调强放疗。OS为总体生存，ROC曲线为受试者工作特征曲线
图4 预测采取IMRT＋后装治疗宫颈癌患者3、5年OS率的列线图预测模型的校准曲线与理想曲线图(图4A：3年OS率；图4B：5年OS率) 注：IMRT为调强放疗，OS为总体生存
图5 采取IMRT＋后装治疗宫颈癌患者的预后危险分层系统图 注：采递归分割分析法对采取IMRT＋后装治疗宫颈癌患者的预后风险进行预后危险分层系统构建。IMRT为调强放疗
表3 不同预后危险分层系统的风险组FIGO临床分期为Ⅰ～Ⅳ期宫颈癌患者的3、5年OS率比较[例数(%)]
组别 Ⅰ期 Ⅱ期 Ⅲ期 Ⅳ期
例数 3年OS 5年OS 例数 3年OS 5年OS 例数 3年OS 5年OS 例数 3年OS 5年OS
极低风险组 10 10(100.0) 9(90.0) 60 57(95.0) 52(86.7) 14 10(71.4) 9(64.3) 4 4(100.0) 3(75.0)
低风险组 5 5(100.0) 4(80.0) 50 45(90.0) 37(74.0) 33 25(75.8) 21(63.6) 5 4(80.0) 4(80.0)
中风险组 5 5(100.0) 4(80.0) 22 19(86.4) 12(54.5) 14 5(35.7) 3(21.4) 5 2(40.0) 1(20.0)
高风险组 4 4(100.0) 2(50.0) 10 6(60.0) 3(30.0) 9 3(33.3) 1(11.1) 8 1(12.5) 0(0)
χ2值   0 2.78   11.37 19.00   10.36 13.57   10.50 11.85
P值   1.000 0.427   0.010 <0.001   0.016 0.004   0.015 0.008
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